Deciding Together?:Best Interests and Shared Decision-Making in Paediatric Intensive Care

In the western healthcare, shared decision making has become the orthodox approach to making healthcare choices as a way of promoting patient autonomy. Despite the fact that the autonomy paradigm is poorly suited to paediatric decision making, such an approach is enshrined in English common law. When reaching moral decisions, for instance when it is unclear whether treatment or non-treatment will serve a child’s best interests, shared decision making is particularly questionable because agreement does not ensure moral validity. With reference to current common law and focusing on intensive care practice, this paper investigates what claims shared decision making may have to legitimacy in a paediatric intensive care setting. Drawing on key texts, I suggest these identify advantages to parents and clinicians but not to the child who is the subject of the decision. Without evidence that shared decision making increases the quality of the decision that is being made, it appears that a focus on the shared nature of a decision does not cohere with the principle that the best interests of the child should remain paramount. In the face of significant pressures toward the displacement of the child’s interests in a shared decision, advantages of a shared decision to decisional quality require elucidation. Although a number of arguments of this nature may have potential, should no such advantages be demonstrable we have cause to revise our commitment to either shared decision making or the paramountcy of the child in these circumstances

Exploring the Conformational Transitions of Biomolecular Systems Using a Simple Two-State Anisotropic Network Model

Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results. © 2014 Das et al

Genome-Wide Diet-Gene Interaction Analyses for Risk of Colorectal Cancer

Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3) and processed meat consumption (OR = 1.17; p = 8.7E-09), which was consistently observed across studies (p heterogeneity = 0.78). The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively) and null among those with the GG genotype (OR = 1.03). Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention. © 2014

Developing search strategies for clinical practice guidelines in SUMSearch and Google Scholar and assessing their retrieval performance

<p>Abstract</p> <p>Background</p> <p>Information overload, increasing time constraints, and inappropriate search strategies complicate the detection of clinical practice guidelines (CPGs). The aim of this study was to provide clinicians with recommendations for search strategies to efficiently identify relevant CPGs in SUMSearch and Google Scholar.</p> <p>Methods</p> <p>We compared the retrieval efficiency (retrieval performance) of search strategies to identify CPGs in SUMSearch and Google Scholar. For this purpose, a two-term GLAD (GuideLine And Disease) strategy was developed, combining a defined CPG term with a specific disease term (MeSH term). We used three different CPG terms and nine MeSH terms for nine selected diseases to identify the most efficient GLAD strategy for each search engine. The retrievals for the nine diseases were pooled. To compare GLAD strategies, we used a manual review of all retrievals as a reference standard. The CPGs detected had to fulfil predefined criteria, e.g., the inclusion of therapeutic recommendations. Retrieval performance was evaluated by calculating so-called diagnostic parameters (sensitivity, specificity, and "Number Needed to Read" [NNR]) for search strategies.</p> <p>Results</p> <p>The search yielded a total of 2830 retrievals; 987 (34.9%) in Google Scholar and 1843 (65.1%) in SUMSearch. Altogether, we found 119 unique and relevant guidelines for nine diseases (reference standard). Overall, the GLAD strategies showed a better retrieval performance in SUMSearch than in Google Scholar. The performance pattern between search engines was similar: search strategies including the term "guideline" yielded the highest sensitivity (SUMSearch: 81.5%; Google Scholar: 31.9%), and search strategies including the term "practice guideline" yielded the highest specificity (SUMSearch: 89.5%; Google Scholar: 95.7%), and the lowest NNR (SUMSearch: 7.0; Google Scholar: 9.3).</p> <p>Conclusion</p> <p>SUMSearch is a useful tool to swiftly gain an overview of available CPGs. Its retrieval performance is superior to that of Google Scholar, where a search is more time consuming, as substantially more retrievals have to be reviewed to detect one relevant CPG. In both search engines, the CPG term "guideline" should be used to obtain a comprehensive overview of CPGs, and the term "practice guideline" should be used if a less time consuming approach for the detection of CPGs is desired.</p

Clinical Utility of Random Anti–Tumor Necrosis Factor Drug–Level Testing and Measurement of Antidrug Antibodies on the Long-Term Treatment Response in Rheumatoid Arthritis

Objective: To investigate whether antidrug antibodies and/or drug non-trough levels predict the long-term treatment response in a large cohort of patients with rheumatoid arthritis (RA) treated with adalimumab or etanercept and to identify factors influencing antidrug antibody and drug levels to optimize future treatment decisions.  Methods: A total of 331 patients from an observational prospective cohort were selected (160 patients treated with adalimumab and 171 treated with etanercept). Antidrug antibody levels were measured by radioimmunoassay, and drug levels were measured by enzyme-linked immunosorbent assay in 835 serial serum samples obtained 3, 6, and 12 months after initiation of therapy. The association between antidrug antibodies and drug non-trough levels and the treatment response (change in the Disease Activity Score in 28 joints) was evaluated.  Results: Among patients who completed 12 months of followup, antidrug antibodies were detected in 24.8% of those receiving adalimumab (31 of 125) and in none of those receiving etanercept. At 3 months, antidrug antibody formation and low adalimumab levels were significant predictors of no response according to the European League Against Rheumatism (EULAR) criteria at 12 months (area under the receiver operating characteristic curve 0.71 [95% confidence interval (95% CI) 0.57, 0.85]). Antidrug antibody–positive patients received lower median dosages of methotrexate compared with antidrug antibody–negative patients (15 mg/week versus 20 mg/week; P = 0.01) and had a longer disease duration (14.0 versus 7.7 years; P = 0.03). The adalimumab level was the best predictor of change in the DAS28 at 12 months, after adjustment for confounders (regression coefficient 0.060 [95% CI 0.015, 0.10], P = 0.009). Etanercept levels were associated with the EULAR response at 12 months (regression coefficient 0.088 [95% CI 0.019, 0.16], P = 0.012); however, this difference was not significant after adjustment. A body mass index of ≥30 kg/m2 and poor adherence were associated with lower drug levels.  Conclusion: Pharmacologic testing in anti–tumor necrosis factor–treated patients is clinically useful even in the absence of trough levels. At 3 months, antidrug antibodies and low adalimumab levels are significant predictors of no response according to the EULAR criteria at 12 months

The use of mesenchymal stem cells for cartilage repair and regeneration: a systematic review.

BACKGROUND: The management of articular cartilage defects presents many clinical challenges due to its avascular, aneural and alymphatic nature. Bone marrow stimulation techniques, such as microfracture, are the most frequently used method in clinical practice however the resulting mixed fibrocartilage tissue which is inferior to native hyaline cartilage. Other methods have shown promise but are far from perfect. There is an unmet need and growing interest in regenerative medicine and tissue engineering to improve the outcome for patients requiring cartilage repair. Many published reviews on cartilage repair only list human clinical trials, underestimating the wealth of basic sciences and animal studies that are precursors to future research. We therefore set out to perform a systematic review of the literature to assess the translation of stem cell therapy to explore what research had been carried out at each of the stages of translation from bench-top (in vitro), animal (pre-clinical) and human studies (clinical) and assemble an evidence-based cascade for the responsible introduction of stem cell therapy for cartilage defects. This review was conducted in accordance to PRISMA guidelines using CINHAL, MEDLINE, EMBASE, Scopus and Web of Knowledge databases from 1st January 1900 to 30th June 2015. In total, there were 2880 studies identified of which 252 studies were included for analysis (100 articles for in vitro studies, 111 studies for animal studies; and 31 studies for human studies). There was a huge variance in cell source in pre-clinical studies both of terms of animal used, location of harvest (fat, marrow, blood or synovium) and allogeneicity. The use of scaffolds, growth factors, number of cell passages and number of cells used was hugely heterogeneous. SHORT CONCLUSIONS: This review offers a comprehensive assessment of the evidence behind the translation of basic science to the clinical practice of cartilage repair. It has revealed a lack of connectivity between the in vitro, pre-clinical and human data and a patchwork quilt of synergistic evidence. Drivers for progress in this space are largely driven by patient demand, surgeon inquisition and a regulatory framework that is learning at the same pace as new developments take place

Application of Bayesian network structure learning to identify causal variant SNPs from resequencing data

Using single-nucleotide polymorphism (SNP) genotypes from the 1000 Genomes Project pilot3 data provided for Genetic Analysis Workshop 17 (GAW17), we applied Bayesian network structure learning (BNSL) to identify potential causal SNPs associated with the Affected phenotype. We focus on the setting in which target genes that harbor causal variants have already been chosen for resequencing; the goal was to detect true causal SNPs from among the measured variants in these genes. Examining all available SNPs in the known causal genes, BNSL produced a Bayesian network from which subsets of SNPs connected to the Affected outcome were identified and measured for statistical significance using the hypergeometric distribution. The exploratory phase of analysis for pooled replicates sometimes identified a set of involved SNPs that contained more true causal SNPs than expected by chance in the Asian population. Analyses of single replicates gave inconsistent results. No nominally significant results were found in analyses of African or European populations. Overall, the method was not able to identify sets of involved SNPs that included a higher proportion of true causal SNPs than expected by chance alone. We conclude that this method, as currently applied, is not effective for identifying causal SNPs that follow the simulation model for the GAW17 data set, which includes many rare causal SNPs

A prospective observational cohort study comparing the treatment effectiveness and safety of ciclosporin, dupilumab and methotrexate in adult and paediatric patients with atopic dermatitis: results from the UK–Irish A-STAR register

\ua9 The Author(s) 2024.Background The main conventional systemic treatments for atopic dermatitis (AD) are methotrexate (MTX) and ciclosporin (CyA). Dupilumab was the first novel systemic agent to enter routine clinical practice. There are no head-to-head randomized controlled trials or real-world studies comparing these agents directly. Network meta-analyses provide indirect comparative efficacy and safety data and have shown strong evidence for dupilumab and CyA. Objectives To compare the real-world clinical effectiveness and safety of CyA, dupilumab and MTX in AD. Methods We compared the effectiveness and safety of these systemic agents in a prospective observational cohort study of adult and paediatric patients recruited into the UK–Irish Atopic eczema Systemic TherApy Register (A-STAR). Treatment effectiveness measures included Eczema Area and Severity Index (EASI), Patient-Oriented Eczema Measure (POEM), Peak Pruritus Numerical Rating Scale (PP-NRS), Dermatology Life Quality Index (DLQI) and children’s DLQI (cDLQI). The minimum duration of treatment was 28 days and follow-up was 12 months. Adjusted Cox-regression analysis was used to compare the hazard ratios of achieving EASI-50, EASI-75 and EASI-90 over time, and linear mixed-effects models were used to estimate changes in efficacy scores. Treatment safety was assessed by examining adverse events (AEs) at follow-up visits. Results We included 488 patients (311 adults and 177 children/adolescents) on dupilumab (n=282), MTX (n=149) or CyA (n=57). CyA and MTX were primarily used as the first-line treatment, while dupilumab was mainly a second-line systemic treatment as per UK National Institute of Clinical and Care Excellence (NICE) recommendations. EASI-50, EASI-75 and EASI-90 were achieved more rapidly in the dupilumab and CyA groups compared with MTX. After adjustment for previous severity, the reduction in EASI, POEM, PP-NRS and DLQI was greater for patients treated with dupilumab compared with MTX. In patients with severe disease the reduction in EASI, POEM and PP-NRS was even greater with CyA. The incidence rates of AEs were similar across groups (734, 654 and 594 per 10 000 person-month on CyA, dupilumab and MTX, respectively). Conclusions This real-world comparison of CyA, dupilumab and MTX in AD suggests that dupilumab is consistently more effective than MTX and that CyA is most effective in very severe disease within 1 year of follow-up

β-Blocker after severe traumatic brain injury is associated with better long-term functional outcome: a matched case control study

PURPOSE: Severe traumatic brain injury (TBI) is the predominant cause of death and disability following trauma. Several studies have observed improved survival in TBI patients exposed to β-blockers, however, the effect on functional outcome is poorly documented.METHODS: Adult patients with severe TBI (head AIS ≥ 3) were identified from a prospectively collected TBI database over a 5-year period. Patients with neurosurgical ICU length of stay &lt;48 h and those dying within 48 h of admission were excluded. Patients exposed to β-blockers ≤ 48 h after admission and who continued with treatment until discharge constituted β-blocked cases and were matched to non β-blocked controls using propensity score matching. The outcome of interest was Glasgow Outcome Scores (GOS), as a measure of functional outcome up to 12 months after injury. GOS ≤ 3 was considered a poor outcome. Bivariate analysis was deployed to determine differences between groups. Odds ratio and 95% CI were used to assess the effect of β-blockers on GOS.RESULTS: 362 patients met the inclusion criteria with 21% receiving β-blockers during admission. After propensity matching, 76 matched pairs were available for analysis. There were no statistical differences in any variables included in the analysis. Mean hospital length of stay was shorter in the β-blocked cases (18.0 vs. 26.8 days, p &lt; 0.01). The risk of poor long-term functional outcome was more than doubled in non-β-blocked controls (OR 2.44, 95% CI 1.01-6.03, p = 0.03).CONCLUSION: Exposure to β-blockers in patients with severe TBI appears to improve functional outcome. Further prospective randomized trials are warranted.</p

Association of HLA class I with severe acute respiratory syndrome coronavirus infection

BACKGROUND: The human leukocyte antigen (HLA) system is widely used as a strategy in the search for the etiology of infectious diseases and autoimmune disorders. During the Taiwan epidemic of severe acute respiratory syndrome (SARS), many health care workers were infected. In an effort to establish a screening program for high risk personal, the distribution of HLA class I and II alleles in case and control groups was examined for the presence of an association to a genetic susceptibly or resistance to SARS coronavirus infection. METHODS: HLA-class I and II allele typing by PCR-SSOP was performed on 37 cases of probable SARS, 28 fever patients excluded later as probable SARS, and 101 non-infected health care workers who were exposed or possibly exposed to SARS coronavirus. An additional control set of 190 normal healthy unrelated Taiwanese was also used in the analysis. RESULTS: Woolf and Haldane Odds ratio (OR) and corrected P-value (Pc) obtained from two tails Fisher exact test were used to show susceptibility of HLA class I or class II alleles with coronavirus infection. At first, when analyzing infected SARS patients and high risk health care workers groups, HLA-B*4601 (OR = 2.08, P = 0.04, Pc = n.s.) and HLA-B*5401 (OR = 5.44, P = 0.02, Pc = n.s.) appeared as the most probable elements that may be favoring SARS coronavirus infection. After selecting only a "severe cases" patient group from the infected "probable SARS" patient group and comparing them with the high risk health care workers group, the severity of SARS was shown to be significantly associated with HLA-B*4601 (P = 0.0008 or Pc = 0.0279). CONCLUSIONS: Densely populated regions with genetically related southern Asian populations appear to be more affected by the spreading of SARS infection. Up until recently, no probable SARS patients were reported among Taiwan indigenous peoples who are genetically distinct from the Taiwanese general population, have no HLA-B* 4601 and have high frequency of HLA-B* 1301. While increase of HLA-B* 4601 allele frequency was observed in the "Probable SARS infected" patient group, a further significant increase of the allele was seen in the "Severe cases" patient group. These results appeared to indicate association of HLA-B* 4601 with the severity of SARS infection in Asian populations. Independent studies are needed to test these results